摘要
岩体结构面是影响岩体稳定性的重要因素,对其信息的准确高效提取是开展地质研究和预测地质灾害的重要基础。本文结合无人机三维激光扫描在岩体结构面识别方面的研究现状,为解决识别精度不高、边界提取不准确等问题,着重分析影响结构面识别精度的因素,并从法向量计算、点云聚类和边界二次精细化处理三方面对识别精度加以改进,然后进行野外结构面提取验证。结果表明,本文提出的识别技术精度较高,为结构面信息的智能化高效提取提供了一种可靠的应用方法。
Rock mass discontinuity is an important factor affecting the stability of rock mass.The accurate and efficient extraction of its information is an important basis for geological research and prediction of geological disasters.In this paper,combined with the research status of UAV 3D laser scanning in rock mass discontinuity recognition,in order to solve the problems of low recognition accuracy and inaccurate boundary extraction,the factors affecting the accuracy of discontinuity recognition are emphatically analyzed,and the recognition accuragy is improved from three aspects:normal vector calculation,point cloud clustering and boundary secondary refinement processing,and then the field verification of rock mass discontinuity is carried out.The results show that the method proposed in this paper has high accuracy,and provides a reliable method for intelligent and efficient extraction of structural plane information.
作者
闫志港
Yan Zhigang(Suqian Zeda Vocational&Technical College,Suqian 223800,China)
出处
《工程勘察》
2023年第10期52-56,共5页
Geotechnical Investigation & Surveying
关键词
无人机
三维激光扫描
岩体结构面
霍夫变换
点云聚类
UAV
3D laser scanning
rock mass structural plane
Hough transform
point cloud clustering
